A linear regression model was applied to identify loci that were differentially methylated with respect to anti-peptide antibody titers and with IFN-γ production. The data were summarized using unsupervised-learning methods: hierarchical clustering and principal-component analysis. Pathways and networks involved were predicted by Ingenuity Pathway Analysis. We observed that the profile of DM loci separated subjects in regards to the levels of immune responses. Canonical pathways and networks related to metabolic and immunological functions were found to be involved. The data suggest that it is feasible to correlate methylation signatures in pre-treatment PBMCs with immune responses post-treatment in cancer patients going through standard-of-care chemotherapy. Larger and prospective studies that focus on DM loci in PBMCs is warranted to develop pre-screening biomarkers before BC vaccination.Immune response to a given antigen, particularly in cancer patients, is complex and is controlled by various genetic and environmental factors. Identifying biomarkers that can predict robust response to immunization is an urgent need in clinical cancer vaccine development. Given the involvement of DNA methylation in the development of lymphocytes, tumorigenicity and tumor progression, we aimed to analyze pre-vaccination DNA methylation profiles of peripheral blood mononuclear cells (PBMCs) from breast cancer subjects vaccinated with a novel peptide-based vaccine referred to as P10s-PADRE. This pilot study was performed to evaluate whether signatures of differentially methylated (DM) loci can be developed as potential predictive biomarkers for prescreening subjects with cancer who will most likely generate an immune response to the vaccine. Genomic DNA was isolated from PBMCs of eight vaccinated subjects, and their DNA methylation profiles were determined using InfiniumClinical Trial Registration:www.ClinicalTrials.gov, Identifier: NCT02229084. We have developed and are clinically testing a cancer vaccine that targets tumor-associated carbohydrate antigens (TACAs), using a carbohydrate-mimicking peptide (CMP) as an immunogen , 2. ThisEpigenetic changes play crucial roles in tumor development and progression. Aberrant DNA methylation exerts significant impact on the regulation of genes involved in tumorigenesis and tumor progression –11. A coIn this study, we sought to determine whether it is possible to define a predictive signature based on differentially methylated loci that can be used to select breast cancer patients who will most likely generate an immune response after vaccination.http://clinicaltrials.gov (NCT02229084). The study was first released on clinicaltrials.gov on 08/26/2014. The IRB was approved on 12/02/2014 and the trial was opened to enrollment on 01/14/2015. The first subject was enrolled on 02/26/2015. Women 18 years of age or older, of all races, with clinical stage I, II or III ER-positive breast cancer were eligible, and subjects were enrolled after providing written informed consent. P10s-PADRE vaccine was given in combination with neoadjuvant chemotherapy in eligible female BC subjects. BC patients were excluded from the trial if they had ER-negative, HER2-positive, inflammatory, metastatic disease, or were pregnant, breast-feeding, with autoimmune diseases, immunosuppressed, or receiving systemic corticosteroids (except those received as antiemetics or for hypersensitivity reactions related to chemotherapy). The patients were recruited from the Breast Cancer Clinic at the Winthrop P. Rockefeller Cancer Institute (WPRCI) at the UAMS campus, and from the Oncology Clinic of the Highlands Oncology Group (HOG) in Northwest Arkansas. For this study, we considered four different vaccination schedules, named A, B, C, and D, that evaluated the feasibility of eliciting an adequate immune response when the vaccine was administered with neoadjuvant chemotherapy. Each schedule had five subjects enrolled. The patients were immunized by administration of three injections of P10s-PADRE vaccine over a 3-weeks period at a dose of 500 μg in a final volume of 2 mL (1 mL peptide and 1 mL of adjuvant) per subcutaneous injection. Patients receiving neoadjuvant chemotherapy were administered doxorubicin (60 mg/m2) and cyclophosphamide (600 mg/m2) every 3 weeks for four cycles followed by docetaxel (75 mg/m2) every 3 weeks for four cycles. The timing of immunizations relative to chemotherapy and blood draws used for antibody and IFN-γ detection for each schedule is shown in This study is part of a single-arm multi-site Phase Ib clinical trial that evaluates the safety, tolerability and feasibility of eliciting adequate IgG response with P10s-PADRE vaccine and MONTANIDE™ ISA 51 VG as an adjuvant. P10s-PADRE peptide synthesis and vaccination was described before  multi-spot V-PLEX® assay system  according to manufacturer's instructions as a part of the efforts to determine the levels of multiple cytokines in the serum samples collected. The proinflamatory panel 1 (human) kit, which includes IFN-γ, IL-1β, Il-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, and TNF-α, was used for cytokine measurements. Briefly, aliquots of serum samples were thawed, diluted 1:2 with Diluent 2 , and added to the V-PLEX plates along with standards. The plates were shaken at 700 rpm and incubated overnight at 4°C. After washing the plates 3 times with phosphate-buffered saline plus 0.05% Tween-20 (PBS-T), 25 μL of detection antibody was added to each well. The plate was then placed on a plate shaker and mixed at 700 rpm for 2 h at room temperature. Following incubation, the plate was washed 3 times with PBS-T and 150 μL of 2X Read Buffer was added to each well. The plate was analyzed using the MSD Electrochemiluminescence (ECL) charge-coupled device (CCD) and QuickPlex SQ 120 imager and the results were reported using the Discovery Workbench 4.0 software (MSD). The pre-immune (collected at week 1) and post-immune sera  in a volume equal to the volume of collected blood was transferred into 50-ml conical centrifuge tube. Then, blood was carefully layered onto the Histopaque-1077 at a ratio of 1:1. The mixture was then centrifuged at 400 ®, and methylation values were determined for all probes using the GenomeStudio Methylation module (Illumina).Pre-immune PBMC samples from select subjects were thawed and DNA was isolated using the Gentra Puregene Cell Kit  according to the manufacturer's protocol. Briefly, approximately 1.5 million cells were lysed and processed to remove cellular byproducts. DNA was isolated by ethanol precipitation to a volume of 100 μL. The samples were quantified using Quant-iT PicoGreen dsDNA Assay Kit , and diluted in TE buffer  to a concentration of 20 ng/μL in 40 μL (800 ng). 500 ng of genomic DNA from each patient sample was bisulfite-treated and purified using the EZ DNA Methylation-Gold kit  according to the manufacturer's instructions. Genome-wide DNA methylation was assessed in bisulfite-converted genomic DNA using the Infinium MethylationEPIC BeadChip array , following the Infinium HD Methylation Assay Protocol User's Guide provided by Illumina. Processed BeadChips were scanned on an Illumina iScanp > 0.01 and rsSNPs were removed using this software. DNA methylation levels were reported as β values, which are measurements of the degree of methylation at a specific CpG locus that range from zero (0%) to one (100%), where zero indicates a non-methylated probe and one indicates a fully methylated probe. The .idat files were transferred into Partek Genomics Suite  and probes located in the X and Y chromosomes and those with polymorphic targets and cross-hybridization potential  were fii = μ + log2 (fold change in Ab titer) + εi, Yi represents the M-value of the ith subject, μ the intercept, fold change in Ab titer the independent variable and εi the error term. Moreover, through an alternative analysis, we correlated the subjects' methylomes to their IFN-γ levels using the same statistical model with fold change in IFN-γ concentration of serum substituted for fold change in Ab titer, as follows:The identification of differentially methylated CpGs (DM CpGs) among responders and non-responders to P10s-PADRE IgG response was done via Method of Moments using the following linear regression model applied to each CpG site: Y2 (Ab titer) or log2 (IFN-γ), respectively, as independent variables. Statistical significance was defined using an alpha ≤ 0.001 significance level to adjust for the multiple CpG sites being tested without overinflating Type II  error in this small-scale pilot study.A CpG site was identified as DM with respect to either Ab titer or IFN-γ levels if it was statistically significant in the linear regression model with either log® Pathway Analysis (IPA®) tool, version 01–12. IPA is based on the Ingenuity Knowledge Base that contains manually curated content related to studies and observations from biomedical literature and also integrated from other data bases  were selected, the number of molecules per network was 35, the confidence chosen was experimentally observed (not predicted), information associated to tissues and cell lines and the species was human.In order to interpret the BeadChip array data, we used Ingenuityta bases . The lisp-value in the canonical pathways depends on the size of the pathway and is less significant when the proportion of the reference set molecules present in the pathway is larger. Another measurement is the ratio and it is estimated by considering the number of genes from the uploaded data set that are on the canonical pathway and is divided by the total number of genes present in the pathway, hence the ratio shows the percentage of genes in a given pathway that were also present in the uploaded gene list.The networks are shown as genes or their products (nodes) and their biological relationships (edges). Networks contain a score based on the number of eligible molecules they contain. The score is calculated through Fisher's Exact Test. The higher the score, the probability to find the molecules present on the network by random chance is lower and considering this, the network with the highest score was the one selected for each analysis. The same test is used for the pathways' discovery. The P ≤ 0.001), and 135 of them mapped into annotated genes as shown in Eight BC patients  were incP-values. Eighty-two out of 182 DM CpGs mapped into the IPA database and were significantly enriched in five affected canonical pathways, including: remodeling of epithelial adherens junctions, CTLA4 signaling in cytotoxic T lymphocytes, NOTCH signaling, tyrosine biosynthesis IV and phenylalanine degradation I , IL-10 (2.23 (±0.61), P = 0.048), and IFN-γ (4.47 (±1.89), P = 0.03). P-values arise from two-tailed one-sample t-tests of log2 transformed data.We measured levels of cytokines IFN-γ, IL-1β, Il-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-α in pre- and post-immune serum samples using a validated multiplex assay. We observed reliable mean fold increases [Mean (±SE)] in IL-6 (1.64 (±0.22), 2 (fold increase in IFN-γ level) as the independent variable, 398 DM CpGs were identified (P ≤ 0.001), of which 324 were mapped into annotated genes  and IGF-1 signaling pathways. GH signaling plays a key role in cancer development and its activation can lead to STAT1, STAT3 and STAT5 signaling . The IGFCancer-related methylation changes are detectable in the DNA of blood cells , suggestThe data presented herein demonstrate a complex interrelationship between pathways involved in immune system, as well as signaling directly affecting tumor progression. However, methylation patterns in baseline PBMCs are associated with post-treatment immune responses that indicate the feasibility of developing predictive signatures based on DM loci to prescreen breast cancer patients who will more likely generate an immune response after therapy. The data warrant further investigation in larger cohorts.https://ega-archive.org) which is hosted at the EBI and the CRG, under study number EGAS00001004211 with accession number EGAD00010001854.The original contributions presented in the study are publicly available. This data can be found here: the European Genome-Phenome Archive . The patients/participants provided their written informed consent to participate in this study.The studies involving human participants were reviewed and approved by Institutional Review Board of the University of Arkansas for Medical Sciences (reference number 202556), and registered with the NIH clinical-trials registry at CH, P-CH, SK, and BM-K performed full methylation analysis and summarized data. FJ, LR, and BM-K conducted the laboratory experiments. ES conducted the statistical analysis. LH, IM, ES, SK, BM-K, and TK-E designed the study. JB, LH, and IM conducted the clinical trial and along with the other authors contributed to the writing of the manuscript.TK-E and BM-K are named as inventors on an institutional patent application filled by UAMS that is related to the content of this manuscript. Therefore, TK-E, BM-K, and UAMS have a potential financial interest in the vaccine used in this clinical trial. No financial or other support of any kind has resulted from this patent application. These financial interests have been reviewed and the clinical trial was performed by approved supervision in accordance with the UAMS conflict of interest policies. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Little is known on how context-specific sedentary behaviors (SB) affect adiposity. This study aimed to investigate compositional associations between context-specific SB and adiposity and estimate the differences in adiposity associated with replacing school and out-of-school SB with physical activity (PA).This study included 336 children and adolescents. Time spent in SB and PA was estimated using multi-day 24-hour raw accelerometer data. SB and PA were specified for school and out-of-school times. Fat mass percentage (FM%) and fat mass index (FMI) were used as adiposity indicators. A compositional isotemporal substitution model was used to estimate differences in adiposity associated with one-to-one reallocations of time from context-specific SB to PA.βilr1 = 0.63, 95% confidence interval [CI] = 0.03–1.22 for FM%; βilr1 = 0.76, 95% CI = 0.03–1.49 for FMI) and girls . Replacing 30 min/day of out-of-school SB with out-of-school light PA decreased FM% by 10.1% (95% CI = 3.3–17.9) and FMI by 14% (95% CI = 2.7–24) in girls. No significant associations were found for school SB.Participants spent approximately two thirds of their school and out-of-school time being sedentary. Relative to the remaining 24-h movement behaviors, significant associations between out-of-school SB and adiposity were found in both boys (A reduction of out-of-school SB in favor of light PA should be advocated as an appropriate target for interventions and strategies to prevent childhood obesity.The online version contains supplementary material available at 10.1186/s12199-021-00932-6. Sedentary behavior (SB) is described as any waking behavior where energy expenditure is equal to or less than 1.5 metabolic equivalents while a person is sitting, reclining, or lying  with a hNumerous studies have investigated the relationship between total SB and adiposity in past decades but their conclusions have been inconsistent . The occAlthough previously published studies have shown that both school and out-of-school SB are independently associated with adiposity indicators , 16, 17,To our knowledge, a study based on 24-h movement behaviors to examine the associations between context-specific SB and adiposity data has not been published. The present study sought to fill this gap by (1) investigating compositional associations between context-specific SB and adiposity and (2) estimating the differences in adiposity associated with replacing school and out-of-school SB with PA in the 24-h movement behavior composition.This observational cross-sectional study included children and adolescents aged 8 to 18 years who were recruited from urban and rural schools across the Czech Republic. The study’s sampling and design details have been reported elsewhere . BrieflySB, PA, and sleep were measured using the wrist-worn ActiGraph accelerometer GT9X Link or wGT3X-BT  which are comparable if count-based metrics are used . ParticiRaw accelerometer data were saved as GT3X files and reintegrated to 5-s periods. Non-wear time was captured with the Choi algorithm  to minimTime spent in SB, LPA, MPA, VPA, and sleep were summed and then normalized to 24 h . We applied the wear time requirement of ≥ 1200 min of a total wear time with ≥ 720 min of awake time, ≥ 320 min of sleep time, and 220–440 min of school time to constitute a valid measurement. In order to cover the whole period of 1 week, participants with a valid set of 7 days and nights and with valid school and out-of-school segments for all the five school days included in the measurement period were included in the final analysis.Adiposity was assessed on the school premises during school hours using the multi-frequency bioelectrical impedance . Fat mass percentage (FM%) and fat mass index (FMI) were used as indicators of adiposity. The multi-frequency bioimpedance analysis method has been previously validated against dual-energy X-ray absorptiometry for assessing adiposity in pediatric population . Partici2) and education level were reported by parents. Missing values (2–6%) were imputed using the k-nearest neighbor imputation algorithm [The several covariates were selected to control for potential cofounding factors. We selected a set of potential confounding factors a priori based on the literature  and baselgorithm .IBM SPSS Statistics version 23  was used to determine the descriptive analyses and to verify the data for further analysis. A CoDA was conducted with R Statistical Software, version 4.0.2  using the robCompositions package. The analysis was performed separately for boys and girls to take into account sexual dimorphism in adiposity .ilr1), which includes all relative information about the one part given the remaining parts of 24-h composition, was used in the analysis [The descriptive statistics of the compositional variables are presented as a robust center  and variation matrix . We used the 9-part 24-h movement behavior composition which takes into account school and out-of-school behaviors  and sleep. The variables of movement behaviors were expressed as isometric log-ratio coordinates and the first pivot coordinate  in the population and to ensure a statistical power of ≥ 80% and an alpha error of 0.05 for regression models with 13 explanatory variables [Differences between sexes were tested using the independent rvations  that occariables .The compositional isotemporal substitution model  was used2 (p < 0.001 for both), respectively, compared with girls. In both age categories, participants spent 64–69% of their school and out-of-school time in SB. Relative to the remaining 24-h movement behaviors, boys spent less time in school MPA, by 2.8 min/day (p = 0.005), and more time in school VPA, by 0.8 min/day (p < 0.001), than girls. Boys also spent less time in out-of-school LPA and out-of-school MPA, by 17.9 min/day (p = 0.011) and 18 min/day (p < 0.001), respectively.The descriptive characteristics of the included participants did not differ from those who were excluded Table S. The chaβilr1 = 0.63, 95% CI = 0.03 to 1.22) and girls . Similar associations were found for FMI for boys  and for girls . Relative to the remaining 24-h movement behaviors, out-of-school LPA was significantly associated with FM%  in girls. No significant associations between movement behaviors during school and adiposity indicators were found.Table Estimated relative differences in adiposity indicators associated with simulated reallocations of time from school and out-of-school SB to PA of different intensities are presented in Tables The findings of the present study provide novel insights into the compositional associations of context-specific SB with adiposity and the changes in adiposity associated with replacing SB with PA. We found that boys and girls spent approximately two thirds of their school and out-of-school time being sedentary. The greater amount of time spent in out-of-school SB was associated with FM% and FMI in both sexes. Replacing out-of-school SB with out-of-school LPA results in favorable changes in adiposity among girls. No significant associations were found for school SB.In line with previous studies , 36, 37,We had no empirical data on SB patterns during school time, so we could only hypothesize that most of the time our participants spent in school SB was accumulated by a few periods of prolonged SB . Prolonged uninterrupted SB is associated with several adverse health outcomes including excess adiposity –42. ConsOut-of-school time also presents numerous opportunities to prevent excess adiposity by reducing SB in favor of PA. Although a plethora of studies show that a favorable adiposity status is associated with at least MPA as part of active transportation to and from school  and orgaz-score [The novel finding of this study is that adiposity could be improved by increasing out-of-school LPA at the expense of time spent in out-of-school SB. This finding corresponds with previous CoDA-based studies showing the favorable difference in adiposity  and bodyz-score  for timez-score . Althougz-score  supportsThe compositional isotemporal substitution model used in the present study found significant differences in adiposity only in girls. Similar to our findings, previously published studies , 50 confTo the best of our knowledge, this is the first study to use CoDA to examine associations between context-specific SB and adiposity indicators. The strength of the study is the availability of raw multi-day 24-h movement data which allowed SB adjustment for PA and sleep duration. There are also some limitations to this study. First, the design of study was cross-sectional with limited ability to draw causality in the associations between 24-h movement behaviors and adiposity. Second, an isotemporal substitution model provides only theoretical estimates of changes in adiposity. Our findings should be, therefore, interpreted with caution and need to be contrasted in experimental designs. Third, although the regression analysis was adjusted for several confounders, there are still several potential endogenous and exogenous factors that have not been considered. Last, although the sample size is comparable with previous studies , 50, 51,The present study is the first to use CoDA when examining associations between context-specific SB and adiposity status in school-aged children and adolescents. We revealed positive (unfavorable) associations between out-of-school SB and adiposity. Based on compositional isotemporal substituting modeling, the present study suggests that adiposity status could be improved by replacing out-of-school SB with out-of-school LPA. No significant associations were found for school SB. This study, therefore, highlights the need for assessing the context-specific SB and to amplify the benefits of LPA in the prevention of excess adiposity. Findings from the present study provide further evidence for public health policy and practices and may help to design more effective strategies to prevent childhood obesity.Additional file 1: Figure S1. Relative difference in fat mass percentage associated with replacing school (left) and out-of-school (right) SB with MPA in boys (top) and girls (bottom). Positive values on the x-axis present time replacement from context-specific SB to MPA, and negative values time replacement from context-specific MPA to SB.Additional file 2: Figure S2. Relative difference in fat mass percentage associated with replacing school (left) and out-of-school (right) SB with VPA in boys (top) and girls (bottom). Positive values on x-axis present time replacement from context-specific SB to VPA, and negative values time replacement from context-specific VPA to SB. Note: The isotemporal substitution model was unable to estimate difference for reallocation between school SB and VPA due to low compositional mean for school VPA among girls.Additional file 3: Table S1. Descriptive characteristics of included and excluded participants.


In contrast, ZOL-Pre+Post rats (20.4% ± 5.0%) showed similar BA% compared to Saline controls (p = 0.731). BIC% revealed a significant increase for ZOL-Post (65.8% ± 16.9%) and ZOL-Pre+Post (68.3% ± 10.0%) rats compared with that of Saline controls , while ZOL-Pre rats (55.6% ± 19%) showed a BIC% comparable to that of Saline controls (p = 0.408). Our results suggest that receiving intravenous ZOL treatment before or after implant placement enhances peri-implant bone responses in terms of bone area. However, the effect of different ZOL treatment regimens on BIC% was found to be inconclusive.We evaluated the response to peri-implant bone placed in the femoral condyle of osteoporotic rats, following intravenous zoledronate (ZOL) treatment in three settings: pre-implantation (ZOL-Pre), post-implantation (ZOL-Post), and pre- + post-implantation (ZOL-Pre+Post). Twenty-four female Wistar rats were ovariectomized (OVX). After 12 weeks, the rats received titanium implants in the right femoral condyle. ZOL  was administered to six rats 4 weeks pre-implantation and was stopped at implant placement. To another six rats, ZOL was given post-implantation and continued for 6 weeks. Additional six rats received ZOL treatment pre- and post-implantation. Control animals received weekly saline intravenous injections. At 6 weeks post-implantation, samples were retrieved for histological evaluation of the percentage of bone area (%BA) and of the percentage of bone-to-implant contact (%BIC). BA% for ZOL-Pre (29.6% ± 9.0%) and ZOL-Post (27.9% ± 5.6%) rats were significantly increased compared to that of the controls (17.3% ± 3.9%,  The worldwide use of dental implants is still increasing, as these fixtures offer many advantages above the more conventional prosthetic reconstruction of lost teeth . This isThe pharmaceutical treatment of osteoporosis includes the use of a wide range of drugs , calcitonin, parathyroid hormone, and calcium supplements) as well as various routes of administration  . BesidesTherefore, the purpose of the present study was to evaluate the bone response to titanium implants placed in osteoporotic rats treated with intravenous ZOL at three different times  compared to non-treated controls.All animal experiments in the present study were in accordance to the guidelines  for animal care and conformed to the ARRIVE guidelines. The Animal Ethics Committee at King Saud University, Saudi Arabia, approved the present study (No. 4/67/389683). Twenty-four female Wistar rats (weight of ~250 g) were used. The animals were housed in standardized rat cages  maintained in a laboratory environment with controlled temperature (22–24 °C) and humidity (45–55%) and 12 hourly light and dark cycles. All animals had ad libitum access to a standard rat chow diet and water. All rats were subjected to bilateral ovariectomy (OVX) procedures under general anesthesia (GA) to induce an osteoporotic condition as previously described .2). Standard deviation (s) was 12.5, effect size (d) was 15, C was 7.85 (resulting from 1-β = 0.8 and α = 0.05). The final result was 24 rats (one implant per rat).The power analysis of sample size was done using the formula (n1 = n2 = n3 = 1 + 2 × c(s/d)® Polyglactin 910, Ethicon, Johnson & Johnson, New Brunswick, NJ, USA). For the anti-osteoporotic treatment, a ZOL injection  was prepared and administered intravenously via the tail vein, as described previously [ZOL-Pre: weekly ZOL administration (0.04 mg/kg body weight) in the 4 weeks prior to implant placement .ZOL-Post: weekly ZOL administration in the 6 weeks from implant placement until the end of the study (=6 weeks) .ZOL-Pre+Post: weekly ZOL administration from 4 weeks prior to implant placement until the end of the study (=10 weeks).Saline: weekly intravenous injection with 1 mL saline from 4 weeks prior to implant placement until the end of the study; this group was considered the non-treated control.At 12 weeks post-ovariectomy, a sterile condition was applied for the implantation surgery. A single intraperitoneal injection of 0.2 mg/kg xylazine  and 0.5 mg/kg ketamine hydrochloride  was used for general anesthesia. Then, the right rat’s leg was shaved and disinfected using 10% Povidone–iodine . An incision was made over the knee joint to expose the femoral condyle. Then, we drilled a small hole (1.5 mm in diameter and 8 mm in depth) using surgical burs and a rotary handpiece along with saline irrigation. Then, a commercially available mini-implant  was placed in the prepared hole (1 implant per rat). Finally, the skin was sutured with 4-0 resorbable sutures  (pMMA) resin. Thereafter, longitudinal sections (10 µm thick) were prepared using a microtome and stained with methylene blue and basic fuchsin. A light microscope  was used for their observation. Histologic observations were performed by two examiners (AB & JJ). Using the Aperio ScanScope  image extraction tool, individual histology images were extracted in 25% jpg format. An image analysis software  was used to perform blinded histomorphometric measurements for three histological sections per implant (at ×20 objective magnification). The color hue and saturation of bone tissues were selected and standardized to red, while the other tissues were in yellow. Then, bone area (BA%) was measured in a region of interest (ROI) on both sides of the implant, i.e., a rectangular box  that started at the 2nd top implant thread . Bone-top < 0.05.SPSS Statistical Program  was used to perform the descriptive statistics of BA% and BIC%, as mean and standard deviation (SD). Comparisons between test and saline groups were performed using one-way analysis of variance (ANOVA) with Dunnett post-hoc test, with statistical significance of Animals in all groups showed no clinical complications or infections post-implantation. Saline controls: light microscopical examination of the histological sections revealed that the bone of the femoral condyle had an osteopenic appearance, which was characterized by the presence of a limited amount of bone trabeculae as well as a wide spacing between the bone trabeculae A. Bone mZOL-Pre: examination of the histological sections suggested that the amount of bone in the femoral condyle as well as surrounding the implant was increased compared to Saline controls A. This iZOL-Post: a light-microscope assessment indicated features largely similar to those observed in ZOL-Pre rats. The bone amount in the femoral condyle and around the implants was larger compared to that of Saline controls and appeared very similar to that observed in ZOL-Pre rats . RemodelZOL-Pre+Post: histological images suggested enhanced bone formation in the femoral condyle. In contrast to ZOL-Pre and ZOL-Post rats, the increase was mainly seen at the crestal side of the implant and extended about halfway up the implant length A. Areas p = 0.013 and 0.025, respectively, p = 0.731). BIC% values were 55.6% ± 19.0% for ZOL-Pre, 65.8% ± 16.9% for ZOL-Post, 68.3% ± 10.0% for ZOL-Pre+Post, and 43.3% ± 9.6% for Saline controls. Statistical testing revealed a significant difference for ZOL-Post and ZOL-Pre+Post with respect to Saline controls (p = 0.049 and 0.027 resp), while ZOL-Pre showed a BIC% comparable to that of Saline controls . Additionally, BIC% data showed a significant difference when comparing post-implantation and pre+post-implantation ZOL-treated rats to saline controls (p < 0.05).In the present study, the peri-implant bone response was compared in OVX rats, which were treated with ZOL  via intravenous infusion at three different times: pre-implantation, post-implantation, and pre+post-implantation; rats receiving weekly saline injections served as controls. Both bone area (BA%) and bone–implant contact (BIC%) were histomorphometrically evaluated. In comparison to saline controls, the pre- and post-implantation ZOL treatment showed a significant gain of BA%  if they did not receive anti-osteoporotic therapy before implant surgery. Consequently, we decided to investigate the effect of three ZOL administration regimens related to the moment of implant installation. A key aim was to determine whether post-implantation continuation of the administration of ZOL would be more beneficial in comparison with only pre- or post-implantation drug administration. A delay in the delivery of ZOL to the implant site was hypothesized to have less pharmacological benefit than pre-implantation ZOL binding to the target site. In addition, prolonged ZOL administration was supposed to better “treat” the diseased bone at the implant site. In a continuous approach, the preoperative administration of ZOL has to control the unbalanced bone metabolism, while the postoperative administration of ZOL has to enhance bone–implant healing [Our study design for evaluating the peri-implant bone response in osteoporotic animals is distinct from previous studies, which focused on testing the effect of ZOL administration only post-implantation. Our aim was to test different clinical scenarios, as can occur in patients with postmenopausal osteopenia requiring dental implant installation. For example, August et al.  observed healing .However, the above-mentioned hypothesized effect of a continuous approach was not proven. In contrast, an improvement in BA% around the implants was observed for the intravenous administration of ZOL to OVX rats for only 4 weeks pre-implantation or only post-implantation. However, no favorable effect was seen for the continued administration, which led to a BA% comparable to that non-treated osteoporotic rats. The beneficial effect of only pre- or post-implantation administration of ZOL on BA% corroborates other studies. For example, Yoshioka at al.  demonstrOn the other hand, the pre+post-implantation ZOL treatment of osteoporotic rats did not favor BA% increase. An explanation for this finding can be related to the applied doses of ZOL. The effect of nitrogen-containing BPs, like ZOL, on osteoclasts is known to be depending on dose and dose frequency . In addiAs mentioned earlier, the recommended treatment approach for osteoporosis is a once-yearly intravenous infusion of ZOL. In our study, ZOL was administered once weekly for a period of 10 weeks. Therefore, it cannot be excluded that this dosing was too high, resulting in a decreased effect on bone formation. In view of this, it is recommended to determine the alkaline phosphatase (ALP) level in the blood serum of the rats in future studies. This will provide information about the therapeutic effect of ZOL in an osteoporotic condition.The measurements of BIC% showed a significantly higher BIC% in rats receiving post- and pre+post-implantation ZOL treatment compared to saline controls. These data are inconclusive, and their relevance is not evident. These inconsistent observations can be explained by a low remodeling activity of the trabecular bone surrounding the implant bed in all treatment scenarios. How this interferes with bone formation at the implant interface remains elusive. In combination with the relatively short implantation time, it can be assumed that the bone present at the implant surface was mainly already existing bone and not newly deposited bone. In this condition, BIC% represents just the amount of bone present during implant installation. This explanation is in agreement with other studies, which suggested that a follow-up time of 6 weeks is too short, and more than 8 weeks of observation are necessary to detect a possible effect of pharmacological drugs on the interfacial implant–bone response ,47.Additionally, implant location as well seems to have a significant effect on the results. For instance, Cardemil et al. studied the different biological reactions of the tibia and the mandible in rats, both in response to ovariectomy and in response to the ZOL treatment. They reported an increase of BIC in the tibia, whereas the opposite occurred in the mandible . This vaFinally, a comment has to be made regarding the experimental conditions of the current study. Some authors noticed that a high calcium diet may reverse the condition of osteopenia in ovariectomized animals . In our Under the current experimental conditions, our results suggest that receiving intravenous ZOL treatment before or after implant placement enhances peri-implant bone responses in terms of bone area. However, the effect of different ZOL treatment regimens on BIC% was found to be inconclusive. Further, the following recommendations can be made for future studies dealing with implant installation in osteoporotic animals and co-administration of anti-osteoporotic drugs: (1) allow an implantation time longer than 8 weeks and (2) determine ALP blood serum levels to assess the therapeutic efficacy of the anti-osteoporotic drugs.


This meta-analysis aimed at exploring the predictive value of CHA PubMed, Embase, Web of Science, ScienceDirect, Cochrane Library, and Chinese core journals of the CNKI and Wanfang databases were searched to identify all the relevant papers that were published up to January 2020. The data were extracted for pooled odds ratios (ORs) with 95% confidence intervals (CIs), heterogeneity, subgroup, publication bias, and sensitivity analysis. 2DS2-VASc score was related with LAT/LASEC  with high heterogeneity  and LAT  with high heterogeneity . The subgroup analysis demonstrated that the sample size may be the main source of heterogeneity. Although the Begg's funnel plot based on 15 studies for LAT/LASEC (P = 0.029) and 12 studies for LAT (P = 0.046) indicated the presence of publication bias among the included studies, the trim-and-fill method verified the stability of the pooled outcomes. In addition, sensitivity analysis indicated that all effects were stable.  Overall, 15 studies containing 6223 patients with NVAF were enrolled. All studies were evaluated for LAT, and 12 studies were evaluated for LASEC. The pooled analysis using a random-effects model showed that a high CHA2DS2-VASc score is related with LAT and LASEC in patients with NVAF. However, more studies are warranted to address this issue. The results of this meta-analysis showed that the CHA Atrial fibrillation (AF) is a fairly common arrhythmia worldwide, and 33 million people are estimated to be suffering from this condition . Worryin2DS2-VASc is a simple, clinical risk factor-based approach to thromboprophylaxis. Although the CHA2DS2-VASc score has been widely used to evaluate the risk recurrence of AF [2DS2-VASc score can predict LAT/LASEC by analyzing six relevant studies [2DS2-VASc score and the risk of LAT or LASEC, and the discrimination ability of CHA2DS2-VASc score was further determined for the prediction of LAT/LASEC.CHAce of AF  and ischce of AF , there hce of AF  reported studies –15. Neve studies –25 are nThis meta-analysis was based on the preferred reporting items for the systematic review and meta-analysis (PRISMA) project . All dat2DS2-VASc,” “thrombus,” and “fibrillation.” The reference lists of some major articles and reviews were manually checked to avoid missing relevant studies.PubMed, Web of Science, ScienceDirect, Cochrane Library, and the Chinese core journals of the CNKI and Wanfang database were systematically searched to identify relevant studies from inception to January 2020 by using the following search terms: “CHA2DS2-VASc score and LAT/LASEC in patients with AF, and sufficient information to evaluate odds ratios (ORs) with 95% confidence intervals (CIs). Case reports, reviews, conference papers, editorials, and animal studies were excluded. The most informative study was included for the repeated studies carried out among identical research populations. Studies were identified using the above search strategy by two independent reviewers. A third reviewer was consulted when faced with uncertainty regarding eligibility.Studies were included if they satisfied the following criteria: original clinical trial, studies that reported the relation between CHA2DS2-VASc score were collected from each study that met the inclusion criteria.Two reviewers extracted data concerning patient characteristics and clinical outcomes by using a standard data collection form. The first author's name, year of publication, study design, region, paroxysmal AF percentage, age, ample size, number of LAT and LASEC, and CHAThe quality of the included studies was separately assessed by two reviewers by using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool . All eliχ2-based Q-statistic and I2 test. The I2 values of 25%, 50%, and 75% indicated low, moderate, and high levels of heterogeneity, respectively. The fixed-effect model was used if P > 0.1 and I2 < 50%. Otherwise, the random-effects model was used. If heterogeneity exists, the possible reasons were investigated and reported through subgroup analysis. Furthermore, sensitivity analysis was performed to evaluate the robustness of the meta-analysis results. Begg's funnel plot was used to explore publication bias, and the trim-and-fill method was used to adjust the effect of publication bias if present (P < 0.05). A two-sided P < 0.05 was considered statistically significant.The STATA 14.0  was applied to assess statistical significance. The summary effect size was expressed as an OR with corresponding 95% CI. Heterogeneity between studies was assessed using the Cochran The baseline characteristics of fifteen eligible studies in the meta-analysis are summarized in 2DS2-VASc score was related with LAT/LASEC  (P < 0.001) calculated using the trim-and-fill method was consistent with the original analysis  . The triP = 0.064) (P < 0.001) calculated using the trim-and-fill method was consistent with the original analysis  . The triSensitivity analysis showed no noticeable change in the statistical significance of all outcomes by removing the single studies. This finding indicated that all effects were stable  and 122% increased risk for detecting LAT  from higher CHA2DS2-VASc score remains challenging. Some studies have indicated that patients who are categorized as low risk by the CHA2DS2-VASc score  also have a risk of LAT/LASEC [2DS2-VASc score needs to be improved and perfected. Van Chien et al. has increased the predictive ability (χ2) from 3.53 to 33.48 by adding the left atrial volume index and the left atrial negative strain rate in the two-chamber view to the CHA2DS2-VASc score [2DS2-VASc score, as shown in Kim et al.'s study [2DS2-VASc score, as shown in Kapłon-Cieślicka et al.'s study [2DS2-VASc can increase the diagnostic efficiency of the score on LAT/LASEC.Notably, predicting the LAT/LASEC in AF with CHAAT/LASEC , 28–30. Sc score . Similar's study . In addi's study . New stuThis review has several important limitations that need to be acknowledged. First, the eligible articles included in our meta-analysis were restricted to studies published in English and Chinese and likely caused selection bias. Second, complete information regarding some variables, such as renal dysfunction, AF type, and TEE, were lacking in the included article. Third, heterogeneity among studies existed and our analysis should be interpreted with caution.2DS2-VASc score is a valuable predictor for LAT/LASEC in patients with AF. However, further well-designed studies are still warranted to confirm our findings.In conclusion, our meta-analysis suggested that CHA


Caenorhabditis elegans and its cognate bacterial diet comprise a reliable, widespread model to study diet and microbiota effects on host physiology. Nonetheless, how diet influences the rate at which neurons die remains largely unknown. A number of models have been used in C. elegans as surrogates for neurodegeneration. One of these is a C. elegans strain expressing a neurotoxic allele of the mechanosensory abnormality protein 4 (MEC-4d) degenerin/epithelial Na+ (DEG/ENaC) channel, which causes the progressive degeneration of the touch receptor neurons (TRNs). Using this model, our study evaluated the effect of various dietary bacteria on neurodegeneration dynamics. Although degeneration of TRNs was steady and completed at adulthood in the strain routinely used for C. elegans maintenance (Escherichia coli OP50), it was significantly reduced in environmental and other laboratory bacterial strains. Strikingly, neuroprotection reached more than 40% in the E. coli HT115 strain. HT115 protection was long lasting well into old age of animals and was not restricted to the TRNs. Small amounts of HT115 on OP50 bacteria as well as UV-killed HT115 were still sufficient to produce neuroprotection. Early growth of worms in HT115 protected neurons from degeneration during later growth in OP50. HT115 diet promoted the nuclear translocation of DAF-16 (ortholog of the FOXO family of transcription factors), a phenomenon previously reported to underlie neuroprotection caused by down-regulation of the insulin receptor in this system. Moreover, a daf-16 loss-of-function mutation abolishes HT115-driven neuroprotection. Comparative genomics, transcriptomics, and metabolomics approaches pinpointed the neurotransmitter γ-aminobutyric acid (GABA) and lactate as metabolites differentially produced between E. coli HT115 and OP50. HT115 mutant lacking glutamate decarboxylase enzyme genes (gad), which catalyze the conversion of GABA from glutamate, lost the ability to produce GABA and also to stop neurodegeneration. Moreover, in situ GABA supplementation or heterologous expression of glutamate decarboxylase in E. coli OP50 conferred neuroprotective activity to this strain. Specific C. elegans GABA transporters and receptors were required for full HT115-mediated neuroprotection. Additionally, lactate supplementation also increased anterior ventral microtubule (AVM) neuron survival in OP50. Together, these results demonstrate that bacterially produced GABA and other metabolites exert an effect of neuroprotection in the host, highlighting the role of neuroactive compounds of the diet in nervous system homeostasis. How can diet influence neurodegeneration? This study shows that injured neurons in the nematode Caenorhabditis elegans are protected by a supply of the neurotransmitter GABA from their dietary bacteria. Caenorhabditis elegans continues to provide an excellent model to study the relationship between bacteria and host ; mec-4d[e1611]), CF1139 , WCH34 , WCH39 , WCH40 , TU38 (deg-1[u38]), TU3755 (uIs58[Pmec-4mec-4::gfp]), WCH6 , and WCH41  were grown at 20 °C as previously described ; muIs61[Pdaf-16daf-16::gfp]; rol-6[su1006]) animals were placed in plates seeded with E. coli OP50, wild-type HT115, HT115 Δgad mutant, or E. coli supplemented with 2 mM lactate or 2 mM GABA and allowed to lay eggs for 24 hours. The 30 L1 larvae, synchronized 0–2 hours posthatching, were transferred with a mouth pipette to new plates with E. coli HT115 or OP50. Morphological evaluation was performed at 12, 24, and 48 hours posthatching.The 30 L4 CF1139  worms were fed E. coli OP50 or HT115 and allowed to lay embryos for 24 hours. The 30–50 L1 larvae were synchronized as described above and placed on the corresponding diet at 15, 20, or 25 °C.The 30 L4 TU3755 . Because we performed a time course evaluation, animals had different body sizes at each time point. The comparisons were made between animals of the same life stage feeding on the two bacteria. For 12-hour-old animals, pictures were taken in a 60× objective, and for 24- and 48-hour-old animals, pictures were taken in a 40× objective. Experiments were done in triplicate for each time point.Intensity of nuclear expression was estimated as “high” if there were more than 20 GFP-positive nuclei, “medium” between 10 and 19, “low” between 3 and 9, and “undetectable” if there were fewer than 3.One PLM per L4 animal was photographed under a 40× objective. The number of puncta was counted in 100 μm of axon starting from the neuronal soma. Images were visualized in ImageJ (1.46v), and puncta were counted manually.To evaluate the functionality of the AVM mechanoreceptor neuron and PVC interneuron, the ability of animals to respond to gentle touch was tested. Animals were touched at 20 °C.First, animals were synchronized in L1 larvae and placed 30 per NGM plate seeded with different bacteria (mentioned above). Then, in the case of AVM neuron, animals were touched with an eyebrow one time in the head, gently stroking where the pharyngeal bulb lies at 72 hours, whereas for the PVC interneuron, animals were gently touched with an eyebrow 10 times in a head-to-tail fashion every 24 hours after hatching.daf-2ts[e1368]; uIs31 [Pmec-17mec-17::gfp]; mec-4d[e1611]) and TU2773  as a control. L4 animals from both strains were placed on plates seeded with E. coli HT115 and OP50 at 25 and 20 °C. Then, animals were synchronized by taking 30–50 L1 larvae and placing them in three plates for each point of evaluation. Morphology of TRNs  was scored from 12 to 168 hours with intervals of 24 hours.To evaluate the effects of DAF-2 down-regulation on dauer animals, we used the strains WCH34 , the 30 synchronized L1s were placed on individual plates seeded with E. coli HT115 bacteria were inoculated in LB starting from a –80 °C glycerol stock and allowed to grow for 1 hour. Nine different falcon tubes were used to grow bacteria. After the first hour, 1 mL from each tube was taken to measure the OD using a spectrophotometer (Ultraspec 2100). When the cultures reached the desired OD, growth was stopped. This procedure was repeated for each measurement. To obtain the lowest values (0.4/0.6/0.8), cultures were evaluated every hour and, for the rest of the values (0.8–2.0), every 15 or 30 minutes. A total of 200 μL of each culture was inoculated onto six NGM plates. Seeded plates were dried on a laminar flow hood for at least 1 hour. Finally, bacteria were killed on a UV transilluminator  by placing the open plate upside down for 5 minutes using the highest wavelength (365 nm). On three of those plates, 30 synchronized L1 worms were placed. The other three plates were used to test whether bacteria were killed during the protocol. To this end, parts of the lawn of UV-killed bacteria were streaked onto another LB plate to observe whether bacteria grew on the agar within the next 3 days.E. coli OP50 and HT115 bacterial cultures (5 mL) were centrifuged for 15 minutes at 3,500g. The supernatant was sieved twice on 0.2-μm filters using a sterile syringe to separate bacteria in suspension. E. coli OP50 supernatant was used to resuspend E. coli HT115 pellet, and the same was done with E. coli HT115 supernatant on OP50 pellet. Each bacterial suspension was inoculated on NGM plates as described above.Overnight After liquid UV killing, the desired bacteria were mixed with 2 mM GABA, 2 mM glutamate, or 2 mM of L-lactate (Sigma). Bacterial cultures (400 μL) were inoculated in 60-mm NGM plates to cover the entire surface. The next day, 0- to 2-hour synchronized L1 worms were placed in the NGM plates for 24 hours. Animals were moved to freshly prepared plates every 24 hours for 72 hours.E. coli OP50 or HT115 were diluted 1:125 in LB and incubated at 37 °C with shaking O/N. Bacterial cultures were mixed in the indicated proportions and used to prepare plates as described before . Plates with mixed bacteria were irradiated with UV before adding the worms.Bacterial cultures were combined in different proportions with the other bacteria or LB for controls. Liquid LB media growth until OD 0.6 of gad gene are present in E. coli HT115, denominated gadA and gadB. E. coli HT115 mutants were constructed using homologous recombination with PCR products as previously reported ). This step was repeated one more time, and the pellet was resuspended in 2 mL of GAD reagent  and preserved at 4 °C for 2 months maximum. Once the pellet was resuspended, the samples were measured for colorimetric differences (UltraSpect 2100) at 620 nm. Liquid LB treated without bacteria is used as a blank. Average colorimetric value for E. coli HT115 was considered 100% of possible GAD activity for each replicate.Then, 10 mL of each culture was centrifuged at 500E. coli OP50, 25 μg/mL of tetracycline for HT115, and 20 μg/mL of kanamycin and chloramphenicol for HT115Δgad until 107 CFU/mL (3–4 hours).Bacterial cultures were grown in LB media with 25 μg/mL of streptomycin for This reaction consisted of two enzymes that convert a molecule of GABA to succinate by GABA transaminase (GAT) and SSA dehydrogenase (SADH), producing detectable NADPH at 340 nm. Additionally, by inhibition of GAT with aminoethyl hydrogen sulfate, substrate concentrations for each reaction are distinguishable according to OD [NADPH] total = OD [NADPH] GAT + OD [NADPH] SADH.Measurement of GABA was performed following the GABase Sigma protocol with modifications .Reaction was performed in 100-μl final volume containing 1U/mL of GABase previously mixed with 75 mM of potassium phosphate buffer in 25% of glycerol, 100 mM of pyrophosphate potassium buffer, 500 μM of NADP+, 5 mM of a-ketoglutarate, 100 μM of dithiothreitol, 50 mM of aminoethyl sulfate as GAT inhibitor, and 10 uL of each sample. All reactions were performed in 96-well Nunclon plates in a NanoQuant 200 Infinite spectrophotometer for 1 hour at 340 nm and 37 °C. Every run contained positive (5 mM of GABA) and negative controls (no GABAse or no GABA) to be subtracted as background of total NADPH measurement, as well as inhibited reaction with respective controls. The GABA concentration curve was performed in triplicate to measure absorbance from 0 to 5 mM of GABA (Abs = 0.1138 × [GABA] + 0.04522).8 CFU/mL three times in each triplicate. A total of 1 mL of culture was centrifuged at 1,100g  for 10 minutes, and pellet was washed twice with phosphate buffer (1 M KPO4 [pH 6.0]) by pipetting and centrifugation at 3,300g  for 10 minutes. After the last centrifugation, 100 μL of deionized water was added, and samples were treated in a water bath at 95 °C for 15 minutes. Then, a final centrifugation at 1,100g  for 10 minutes separated GABA in the supernatant from bacteria debris. Extracted samples were frozen at –20 °C until immediate use in the reaction the next day.All bacteria culture extractions were performed from 1 × 10mec-4d worms, GAD activity, and GABA production in each bacterium were correlated using one-tailed Pearson’s correlation analysis, and linear regression confirmed the variables’ slope differences.Neuronal morphology for E. coli OP50, 25 μg/mL of tetracycline for E. coli HT115, and 20 μg/mL of kanamycin and chloramphenicol for HT115Δgad at 37 °C for 10 hours. Eight preinocula of 2 mL of liquid LB were set for each bacterial strain, grown overnight, and continued in 35 mL of LB and monitored by OD until required (OD of 1).Bacterial strains were grown in solid LB media with 25 μg/mL of streptomycin for g for 5 minutes to separate bacteria from the media. Bacterial pellet was resuspended in phosphate-buffered saline  and washed twice after centrifugation with PBS at 4,000g for 5 minutes. After the last wash, each pellet was resuspended in 1 mL of cold extraction buffer and pipetted into Eppendorf tubes. The extract solution was prepared by mixing equal volumes of acetonitrile and KH2PO4/NaH2PO4 .Bacterial cultures were centrifuged at 4,000g, and the supernatant was recovered. This step was repeated to optimize metabolite recovery. Samples were dried in a vacuum dryer (Savant) for 60 minutes at 50 °C and 300g.Bacterial membrane permeabilization was performed in two steps. First, Eppendorf tubes were submerged in a liquid nitrogen bath for 2 minutes, defrosted at 4 °C, and vortexed for 30 seconds. This procedure was repeated three times. Secondly, tubes from the first step were sonicated in an ultrasonic water bath  for 15 cycles of 30 seconds on and 30 seconds off at full power. Finally, to obtain the metabolites, samples were centrifuged for 10 minutes at 8,000The 1H NMR spectroscopy and multivariate data analysis were performed at Plataforma Argentina de Biología Estructural y Metabolómica (PLABEM).+/K+ buffer (pH 7.4) containing 0.005% TSP -1-propionate) and 10% D2O. In order to remove any precipitate, samples were centrifugated for 10 minutes at 14,300g at 4 °C. The 500 μL of the centrifuged solution was transferred into a 5-mm NMR tube (Wilmad LabGlass).Samples were randomized and reconstituted in 600 μL of 100 mM NaNMR spectra were obtained at 300 K using a Bruker Avance III 700-MHz NMR spectrometer  equipped with a 5-mm TXI probe. One-dimensional 1H NMR spectra of bacterial extracts were acquired using a standard 1-D noesy pulse sequence (noesygppr1d) with water presaturation ,56. The Quality controls (QC) were prepared as suggested by Dona and colleagues . The 1H Spectroscopic data were processed in Matlab . Spectra were referenced to TSP at 0.0 ppm, and baseline correction and phasing of the spectra were achieved using Imperial College written functions . Each spectrum was reduced to a series of integrated regions of equal width . Noninformative spectral regions containing no metabolite signals, TSP signal, and the interval containing the water signal (between 4.9 and 4.6 ppm) were excluded. Each spectrum was then normalized by the probabilistic quotient method . SpectraThe preprocessed 1H NMR spectral data were imported to SIMCA  for multivariate data analysis. PCA was performed on the Pareto-scaled NMR dataset. OPLS-DA was made to maximize the separation between bacterial groups as a function of neuroprotection. To ensure valid and reliable OPLS-DA models and to avoid overfitting, 200 permutations were carried out. Discriminant features between classes in OPLS-DA models were defined using a combination of loading plot (S-line plot) and VIP plot. Variables met highest p(corr)1 in S-Line plot, and VIP values >1 were selected and validated by spectral raw data examination.E. coli Metabolome Database (ECMDB) [E. coli HT115 and HT115 Δgad extract, respectively.Two-dimensional NMR spectra 1H J-resolved pulse sequences were acquired for resonance assignment purposes. Discriminant features were assigned searching in the  (ECMDB) ,60. The gadA were grown until an OD of 0.6. GAD expression was induced by adding 0.15 mM IPTG to OD-0.6 liquid cultures. After, 1-hour samples of each condition were taken to assess GAD activity and to seed on NGM plates with the appropriate antibiotic and supplemented with 0.1 mM of IPTG.Genetically complemented bacteria with pGE. coli OP50 and HT115 were grown from glycerol stock on LB plates overnight. The next morning, portions of the lawn were cultured on agitation for 4 hours in liquid LB. Liquid cultures (2 mL) were pelleted, and DNA was purified using the UltraClean microbial DNA isolation kit (MO BIO) according to the manufacturer’s instructions.E. coli OP50) and PRJNA526261 (E. coli HT115).Whole-genome sequencing was done at Genome Mayor Sequencing Services. Paired-end reads (2 × 250 bp) were generated using the Illumina MiSeq platform. Sequence data were trimmed using Trimmomatic version 0.27 . TrimmedE. coli OP50 (PRJNA526029) and HT115 (PRJNA526261) were compared between strains by Reciprocal Best Hit analysis using Blast+ [E. coli HT115 strain against OP50. We extracted top hits based on bit scores and E-values. Then, we compared both top hits and selected the best match of each other, named “common sequences.” All the other sequences were defined as “unique.”Annotated proteins in fasta format from assembled genomes of g Blast+ ,65. We rg Blast+  of the pE. coli OP50 and HT115 were grown from glycerol stock on LB plates overnight. The next morning, portions of the lawn were cultured on agitation in liquid LB for 5 hours. Then, bacterial cultures (2 mL) were pelleted for RNA extraction with Max Bacterial Trizol kit (Invitrogen) according to the manufacturer’s protocol.For total RNA isolation, E. coli strain HT115 and three replicates from strain OP50 were analyzed as follows.cDNA libraries for Illumina sequencing were generated by Centro de Genómica y Bioinformática, Universidad Mayor, Chile. cDNA libraries were made with Illumina Truseq stranded mRNA kit according to the manufacturer’s protocol in Illumina HiSeq platform. QC of libraries was made with bioanalyzer, and quantification was done with qPCR StepOnePlus Applied Biosystem. Six sets of lllumina paired-end reads in FASTQ format corresponding to three replicates from https://www.bioinformatics.babraham.ac.uk/projects/fastqc/).Reads with an average quality lower than 30 over four bases, as well as reads shorter than 16 bp, were discarded with Trimmomatic version 0.35 . Pre- anE. coli HT115 and OP50 strains were made using Bowtie2 [E. coli HT115 (accession GCA_004354945.1) and ASM435501v1 from E. coli OP50 (GCA_004355015.1).Mapping and quantification from  Bowtie2  with defp-value (padj) < 0.01 and is reported in This analysis was performed preserving only common sequences; transcript abundance was compared between strains. For this, read quantification was performed with FeatureCounts in Rsubread  in R , and its mean is used as a single biological replicate. Each figure contains at least three experiments  performed as explained before. All the biological replicates are performed spaced from each other from 1 day to 1 week.E. coli HT115, which used 30 animals in total.Each experiment started with at least 30 synchronized worms on each technical triplicate with the exception of the longitudinal study of degeneration on Statistical evaluation was performed using one- or two-way ANOVA with post hoc tests and a Student t test when indicated. Results of all tests are detailed in S1 FigE. coli HT115 bacteria grown to different optical density. The underlying numerical data and statistical analysis for each figure panel can be found in (A and B) All axonal categories (A) and wild-type axons (B) in worms feeding on (TIFF)Click here for additional data file.S2 FigE. coli OP50  and HT115  at 25 °C. The underlying numerical data and statistical analysis for each figure panel can be found in All axonal categories of animals feeding on (TIFF)Click here for additional data file.S3 FigNumber of puncta in 100 μm of PLM axons on each bacterial diet (A) and representative photograph of PLM axons used for quantification. Size bar is 20 μm. The underlying numerical data and statistical analysis for each figure panel can be found in (TIFF)Click here for additional data file.S4 FigE. coli HT115 for 6 (A) and 12 (B) hours with controls of ad libitum E. coli OP50 (C) and HT115 (D) or feeding E. coli OP50 for 6 (E) and 12 (F) hours with controls of ad libitum E. coli OP50 (G) and HT115 (H). The underlying numerical data and statistical analysis for each figure panel can be found in (A–D) All axonal categories of animals feeding (TIFF)Click here for additional data file.S5 Figgad E. coli HT115 (A) and OP50 (B) modified with Gad-expressing plasmids, glutamate, and GABA. The underlying numerical data and statistical analysis for each figure panel can be found in gad, glutamate decarboxylase enzyme gene.(A and B) All axonal categories of animals feeding wild-type and Δ(TIFF)Click here for additional data file.S6 FigE. coli strains OP50 (orange) and HT115 (green) and HT115 Δgad mutant (light gray). Quality controls are displayed in yellow. Model parameters are R2X = 0.787 and Q2 = 0.705. (B and C) OPLS-DA validation by 200 permutations. E. coli HT115 and HT115 Δgad validate model intercepts: R2 =  and Q2 =  (B). Protective E. coli HT115 and nonprotective strains E. coli OP50 and HT115 Δgad validate model intercepts: R2 =  and Q2 =  (C). The underlying numerical data for each figure panel can be found in gad, glutamate decarboxylase enzyme gene; NMR, nuclear magnetic resonance; OPLS-DA, orthogonal projections to latent structures discriminant analysis; PC, principal component.(A) PC score plot derived from 1H NMR spectra indicating metabolic differences between wild-type (TIFF)Click here for additional data file.S7 FigE. coli HT115 extract (red) (B); E. coli HT115 Δgad extract (blue). Spike-in was made adding 5 μL of standard 10 mM twice. The underlying numerical data and statistical analysis for each figure panel can be found in gad, glutamate decarboxylase enzyme gene; NMR, nuclear magnetic resonance.(A and B) 1H NMR spectra of GABA (A) and glutamate (C). (B–D) Spike-in of GABA and glutamate confirms identity of metabolites. (TIFF)Click here for additional data file.S8 Figmec-4d animals feeding on E. coli OP50 supplemented with lactate. The underlying numerical data and statistical analysis for each figure panel can be found in mec-4d, mechanosensory abnormality protein 4.All axonal categories of (TIFF)Click here for additional data file.S9 FigKnown GABA concentration plotted against absorbance values creates a curve for later estimation of GABA in samples. The underlying numerical data can be found in (TIFF)Click here for additional data file.S10 Figmec-4d animals feeding on E. coli HT115 expressing dsRNA for GABA effector systemically (A) and touch neuron autonomously (B). The underlying numerical data and statistical analysis for each figure panel can be found in mec-4d, mechanosensory abnormality protein 4.Complete morphological categories of (TIFF)Click here for additional data file.S11 Figdaf-2(ts); mec-4d animals fed OP50. (D–E) All axonal categories of daf-16; mec-4d animals fed E. coli OP50 (D) and HT115 (E). The underlying numerical data and statistical analysis for each figure panel can be found in daf-2, codes for insulin-like growth factor 1 (IGF-1) receptor; daf-16, ortholog of the Forkhead box transcription factor; mec-4d, mechanosensory abnormality protein 4; PLM, posterior lateral microtubule.(A–C) Neuronal integrity of AVM (A), ALM (B), and PLM (C) neurons of (TIFF)Click here for additional data file.S1 TableE. coli HT115 and HT115 Δgad mutant extracts. D, doublet; dd, double doublet; gad, glutamate decarboxylase enzyme gene; m, multiplet; NMR, nuclear magnetic resonance; S, singlet; t, triplet.(XLSX)Click here for additional data file.S2 TableNeuroprotective (HT115) and no neuroprotective (OP50 and HT115) bacterial extracts. D, doublet; dd, double doublet; m, multiplet; NMR, nuclear magnetic resonance; S, singlet; t, triplet.(XLSX)Click here for additional data file.S3 Tablegad, glutamate decarboxylase enzyme gene. cat, chloramphenicol resistance gene; kan, kanamycin resistance gene.(XLSX)Click here for additional data file.S1 File(XLSX)Click here for additional data file.S2 File(XLSX)Click here for additional data file.S3 FileContains sources of experimental materials, strains, and procedures used in this research. MDAR, Materials Design Analysis Reporting.(DOCX)Click here for additional data file.S1 DatasetNumerical data for every experiment on the manuscript are contained in this dataset. Data for each figure are contained in independent tabs.(XLSX)Click here for additional data file.S2 DatasetStatistical and post hoc analysis for every experiment on the manuscript is contained in this dataset. Data for each figure are contained in independent tabs.(XLSX)Click here for additional data file. 23 Jul 2019Dear Dr Calixto, Thank you for submitting your manuscript entitled "Bacterially produced GABA protects neurons from degeneration" for consideration as a Research Article by PLOS Biology.Your manuscript has now been evaluated by the PLOS Biology editorial staff, as well as by an Academic Editor with relevant expertise, and I am writing to let you know that we would like to send your submission out for external peer review. Please accept my apologies for the long delay in sending this initial decision to you.Before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. 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PLOS Biology is pleased to support the "minimum reporting standards in the life sciences" initiative : **We strongly encourage you to complete the MDAR reporting checklist and return it to us with your full submission, as described above. We would also be very grateful if you could complete this author survey:https://forms.gle/seEgCrDtM6GLKFGQAAdditional background information:https://plos.io/MDARFrameworkInterpreting the MDAR Framework: Please note that your completed checklist and survey will be shared with the minimum reporting standards working group. However, the working group will not be provided with access to the manuscript or any other confidential information including author identities, manuscript titles or abstracts. Feedback from this process will be used to consider next steps, which might include revisions to the content of the checklist. Data and materials from this initial trial will be publicly shared in September 2019. Data will only be provided in aggregate form and will not be parsed by individual article or by journal, so as to respect the confidentiality of responses. Please treat the checklist and elaboration as confidential as public release is planned for September 2019.We would be grateful for any feedback you may have. 23 Aug 2019Dear Dr Calixto,Thank you very much for submitting your manuscript "Bacterially produced GABA protects neurons from degeneration" for consideration as a Research Article at PLOS Biology. Your manuscript has been evaluated by the PLOS Biology editors, by an Academic Editor with relevant expertise, and by three independent reviewers. You will note that reviewer 1, François Leulier, signed his comments.In light of the reviews (below), we will not be able to accept the current version of the manuscript, but we would welcome resubmission of a much-revised version that takes into account the reviewers' comments. We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent for further evaluation by the reviewers.Your revisions should address the specific points made by each reviewer. Having discussed these comments with the Academic Editor, we think you should add more data and analyses where the reviewers have indicated that these are necessary to clarify and solidify your conclusions. Particularly, as pointed out by all reviewers, you should especially clarify how the identified GABA dependent mechanisms relate to the IIS/FOXO signaling mechanisms identified in the manuscript. At this stage, it is not clear if GABA acts through IIS/FOXO or if the action of the HT115 strain on IIS/FOXO is a parallel and GABA independent mechanism.In addition, while we appreciate that confirming your findings in additional models of ageing- or disease-related neurodegeneration, as suggested by reviewer 3 (major point 1), would definitively broaden the scope and appeal of your study, we do not think they are necessary for this paper. Thus, while we will welcome those data if you wish to add them, we will not press for them for further consideration in our journal. Please submit a file detailing your responses to the editorial requests and a point-by-point response to all of the reviewers' comments that indicates the changes you have made to the manuscript. In addition to a clean copy of the manuscript, please upload a 'track-changes' version of your manuscript that specifies the edits made. This should be uploaded as a "Related" file type. You should also cite any additional relevant literature that has been published since the original submission and mention any additional citations in your response. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.http://journals.plos.org/plosbiology/s/file?id=9411/plos-biology-formatting-checklist.pdf. It is helpful if you format your revision according to our requirements - should your paper subsequently be accepted, this will save time at the acceptance stage.Before you revise your manuscript, please review the following PLOS policy and formatting requirements checklist PDF: http://journals.plos.org/plosbiology/s/data-availability) requires that you make available all data used to draw the conclusions arrived at in your manuscript. If you have not already done so, you must include any data used in your manuscript either in appropriate repositories, within the body of the manuscript, or as supporting information . For an example see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.Please note that as a condition of publication PLOS' data policy  to discuss this if you have any questions or concerns, or would like to request an extension. At this stage, your manuscript remains formally under active consideration at our journal; please notify us by email if you do not wish to submit a revision and instead wish to pursue publication elsewhere, so that we may end consideration of the manuscript at PLOS Biology.We expect to receive your revised manuscript within two months. Please email us  The title is too broad since it is not known whether this is an evolutionarly conserved phenomena. It should be clearly stated that these findings were obtained in C. elegans.2) The authors should show that GABA levels and GAD enzymatic levels from all bacterial strains tested here and with HT115 at different growth times correlate with the worm phenotypes and perform appropriate statistical analysis to show the power of that correlation.3) The authors should show which tissue(s) are important for the role of daf-16 in regulating the neuronal phenotypes.4) The authors should attempt to discuss the connection between GABA and the IIS.5) It is intriguing why HT115 is rewired to produce GABA more than other E. coli strains. Could the authors comment on this based on their genomic and transcriptomic data? It would be interesting to see what happens to this worm phenotype when cultured in an OP50 strain where ssa is deleted.6) metabolites are not over-expressed. Change to over-abundant.7) Please correct E. coli K12 or K 12 to K-12. Also, please clarify that HT115 is a K-12 strain and OP50 is a B strain. Finally, state what is the K-12 and B strain used in this study.Reviewer #3: In this manuscript, the authors use the degeneration of C. elegans touch receptor neurons in mec-4(gf) animals as a model to investigate the potential effects of dietary bacteria on necrosis/neurodegeneration during development. They report that some laboratory and environmental bacterial strains exhibit more protective effects against degeneration over others. In particular, among the strains tested, E. Coli HT115 can significantly prevent or protect touch receptor neurons and others in mec-4(gf) and deg-1 animals when compared to E. Coli OP50, which is routinely used for maintaining and culturing C. elegans under laboratory conditions. They further uncover that bacterially produced GABA appears to be critical for the neuronal protection function of HT115. The relationship between gut microbiota and brain function has been a hot topic , and some recent studies highlighted the potential link between gut microbiota and certain neurodegenerative diseases. While the paper does nice job in illustrating the protection effects of HT115 in the mec-4(gf) degeneration model, the paper falls short in dissecting the mechanism of this protection as well as addressing the broad interest of this discovery. Major points1) As mentioned in this manuscript, mec-4(gf) caused necrosis of TRNs through Na+ entry, Ca++ influs, and ROS imbalance. Does the protection effect of HT115 acts through suppressing any of them? if so, is GABA a mediator for this regulation. The mec-4(gf) and deg-1 both cause neuronal degeneration through necrosis, and the degeneration is relevant to their channel functions, which is a very special type of neuodegeneration and may not be relevant to the common causes of neurodegeneration, such as ageing, neuronal injury, and neurodegenerative diseases. Therefore, the conclusions of this study may not been applicable to a broad concept of neurodegeneration. TNR neurons display degeneration during ageing, and there are some established neurodegenerative disease models in C. elegans. It is worth to confirm the board impact of bacterially produced GABA in ageing or disease related neurodegeneration. 2) The study identifies the difference between HT115 and OP50 that renders the neuroprotective effects, which turns out to be GABA, but does not fully explore the mechanisms of dietary uptake of GABA in promoting neuronal health. The authors did show that GABA receptors and related transporters were involved somewhere outside of touch receptor neurons, but where possibly could it be? It is necessary to know which tissues/cells are the primary targets of GABA, and this data is also essential in understanding how GABA functions in HT115 related neuronal protection. In this manuscript, all analyses of GABA receptors/transports were down using RNAi, and it should be conformed by loss-of-function mutants of those genes as well as tissue special rescue experiments. Most of GABA functions are tightly coupled with its concentrations, but it doesn’t seem to be the case in this study. As shown in Fig. 7, in O.P. 50 the GAD enzyme activity and the ability of producing GABA are nearly 50% of that in HT115, but O.P. 50 has no protect effect. In contrast, in Fig.2, 1/100 (1%) dilution of HT115 in O.P. 50, in which the GABA concentration is likely 50%+1% of HT115’s, have almost 50% of protection effects of 100% HTT115. It is difficult to understand that how 1% additional HT115 GABA in O.P. 50, which is already 50% of HT115 GABA, causes such significant changes of phenotypes. To me, it suggests that something else in HT115 may be more important than GABA for its protection effects. The data in Fig. 4 is also difficult to understand, that feeding the animals with HT115 before AVM are born can protect them from degeneration. Does this suggest mec-4(gf) is already expressed and cause the degeneration of the Q lineage before AVM are born? Or HT115 causes a long lasting change, which protects AVM after they are born. If it is the later case, GABA may not be the reason to cause HT115 protection, as GABA neurons are continually generating GABA but failed to protect AVM with O.P.50 feeding. In Fig. 5 it seems DAF-16::GFP only has different in 24 h after hatch when feeding with o.p.50 and h115. Does this mean daf-16 is not required for the protecting effects mentioned in Fig.4 when feeding worms only in the first 12 h after hatch3) The authors also brought DAF-2-DAF-16 signaling into the equation, but it is not genetically clear in what fashion this insulin-like signaling is involved in dietary GABA’s neuroprotective function. daf-2(lf) cause constitutive activity of daf-16, but daf-2(lf) didn’t protect AVM in O.P. 50 feeding , which suggests that daf-16 activation is not sufficient to protect AVM from degeneration. If that is case, the DAF-16::GFP expression change in Fig. 5D may not be relevant to the phenotype. For the data shown in Fig. 5E-F, it shows daf-16 is involved in AVM degeneration but not necessary involved in HT115 protection. 4) HT115 feeding may suppress mec-4(gf) expression to protect the cause of AVM degeneration. It should be straightforward to test this by RT-PCR or in vivo labeling of mec-4. Minor points1) It will be good to test whether feeding mec-4(gf) with different bacteria affects the its lifespan.2) Fig. 5D, was the nuclear DAF-16::GFP expression assessed based on whole animals or was it neuron-specific? It would be helpful to indicate it in the Methods or figure legends.3) Do endogenous GABA expression levels differ between widl-type animals and mec-4d mutants during larval stages? There is a very good GABA antibody for worms, and it should easy to be tested 4) OP50 + pGadA + glutamic aid can protect neurons from degeneration, but not quite comparable to HT115 or HT115 + Gad mutation + pGadA5) Fig. 1E, statistical significance? 4 Dec 2019AttachmentResponse to reviewers NeuroFood.docxSubmitted filename: Click here for additional data file. 9 Jan 2020Dear Dr Calixto,Thank you for submitting your revised Research Article entitled "Bacterially produced metabolites protect C. elegans neurons from degeneration" for publication in PLOS Biology. I have now obtained advice from the original reviewers and have discussed their comments with the Academic Editor. You will note that reviewer 2, Filipe Cabreiro, has signed his comments. Based on the reviews, we will probably accept this manuscript for publication, assuming that you will modify it to address the remaining points raised by reviewer 2 and by us and the Academic Editor. Having discussed reviewer 2’s point 1 with the Academic Editor, we do not think you should necessarily address it experimentally. However, while we agree that many of the originally posted questions and doubts which have not been addressed go beyond the current scope of the manuscript, it would be good if the you could add some few sentences to the Discussion to critically discuss other interpretations of how GABA and lactate production could mediate neuroprotection. Like the reviewers, the Academic Editor thinks you have shown that GABA production is required for neuroprotection, but the mechanism is less clear. For example, it seems that GABA only acts in the context of bacteria being present; therefore, the story is more complicated than presented. The Academic Editor also thinks that, for example, one likely possibility is that GABA and lactate to a large extent actually act within/on the bacteria to allow them to do whatever they do to the host. Another unsolved question is the lack of effect on DAF-16 localization with GABA supplementation. Therefore, we think you should be more critical of your findings and discuss the limitation of your data and alternative interpretations to be addressed in future research. We expect to receive your revised manuscript within two weeks. Your revisions should address the specific points made by each reviewer and by the editors. Please submit the following files along with your revised manuscript:1. 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To submit your revision, please go to Please do not hesitate to contact me should you have any questions.Sincerely,Gabriel Gasque, Ph.D., Senior EditorPLOS Biology------------------------------------------------------------------------DATA POLICY:Please ensure that the figure legends in your manuscript include information on where the underlying data can be found, and ensure your supplemental data file/s has a legend.Please ensure that your Data Statement in the submission system accurately describes where your data can be found. ------------------------------------------------------------------------BLOT AND GEL REPORTING REQUIREMENTS:https://journals.plos.org/plosbiology/s/figures#loc-blot-and-gel-reporting-requirementsFor manuscripts submitted on or after 1st July 2019, we require the original, uncropped and minimally adjusted images supporting all blot and gel results reported in an article's figures or Supporting Information files. We will require these files before a manuscript can be accepted so please prepare and upload them now. Please carefully read our guidelines for how to prepare and upload this data: ------------------------------------------------------------------------Reviewer remarks:Reviewer #1, François Leulier: The authors replying in a satisfactory manner to my previous comments and I feel the manuscript is now ready for publication.Reviewer #2, Filipe Cabreiro: The authors addressed all my previous points.I have a remaining point as a result of their new data and discussion which I think needs to be addressed textually or experimentally if they would like to further support their claims.Minor points:1) I don't fully agree with the discussion provided to support their point related to the low production of GABA in B strains. While the rcs may be lost in the B lineage, GABA is still being detected at low levels in OP50. The authors data shows this - approximatelly 50uM, which is far from being neglectable. Therefore, I don't think the authors can say that OP50 lost its capacity to produce GABA. Also, the authors don't explain why HT115 is a particularly high producer of GABA (approximatelly 8-fold higher) when compared to BW25113 which is another derivative of the parental MG1665 K-12 strain. Is this an unexpected trait that only happened to a very highly modified laboratory strain? How does this compare to the parental "wild-type" K-12 strains MG1655 and W3110. The authors should address this experimentally if possible, or alter their discussion to convey their findings more accurately.2) There is a misspelling in rcsB (the authors named it rscB and rsc) and the nomenclature for K-12 isn't always consistent (sometimes shown as K12).Filipe CabreiroReviewer #3: The revised version of this manuscript is great improved. I especially appreciate the new experiments adding Lactate in this context. I recommend the manuscript for publication 5 Feb 2020AttachmentResponse to reviewers and editors 3.docxSubmitted filename: Click here for additional data file. 18 Feb 2020Dear Dr Calixto,On behalf of my colleagues and the Academic Editor, Carlos Ribeiro, I am pleased to inform you that we will be delighted to publish your Research Article in PLOS Biology. The files will now enter our production system. You will receive a copyedited version of the manuscript, along with your figures for a final review. You will be given two business days to review and approve the copyedit. Then, within a week, you will receive a PDF proof of your typeset article. You will have two days to review the PDF and make any final corrections. If there is a chance that you'll be unavailable during the copy editing/proof review period, please provide us with contact details of one of the other authors whom you nominate to handle these stages on your behalf. 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Please be aware that this policy is in place both to ensure that any press coverage of your article is fully substantiated and to provide a direct link between such coverage and the published work. For full details of our Embargo Policy, please visit Thank you again for submitting your manuscript to PLOS Biology and for your support of Open Access publishing. Please do not hesitate to contact me if I can provide any assistance during the production process.Kind regards,Alice MussonPublication Assistant, PLOS Biologyon behalf ofGabriel Gasque,Senior EditorPLOS Biology